Instructions to use xgemstarx/profile_model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xgemstarx/profile_model2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("xgemstarx/profile_model2") prompt = "a photo of xjiminx" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- b1778484351ccf75c0d1da64a1aac36a1f3ce61d29df11b60d4ff845bdf41aec
- Size of remote file:
- 1 kB
- SHA256:
- d64e43d780f79b2c41c77b3638f3da55c2a3273c6e72a559cfe6fb2b05479b63
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